Inspection Method, Inspection Device, and Recording Medium

The present disclosure relates to an inspection method, an inspection device, and a program.

During the production process of organic EL display panels, various inspections are conducted to maintain product quality.

Among various inspection steps, a DS (Dark Spot) inspection is performed in an inspection step of inspecting display defects in a pixel region to inspect if there are any black stain-like display defects (hereinafter referred to as “seepage defects”) caused by faults in a moisture barrier layer.

In the DS inspection, an operator checks an enlarged image of the pixel region and, if a region (hereinafter referred to as a “seepage region”) where moisture has seeped into a light-emitting layer of the pixel region appears in the image, the operator determines whether the region is a seepage defect according to the size of the seepage region.

However, since display defects of pixel regions include display defects other than seepage defects such as display defects caused by dark dots or the like, the operator also needs to determine a defect mode (hereinafter referred to as a fault mode). Both a determination of the fault mode and a measurement of the size of the seepage region are left to the operator's judgment. Therefore, differences in judgment criteria may occur among operators, and even with the same operator, fluctuations in judgment criteria may occur over time. As a result, there are problems of an occurrence of an overkill where a good product is judged as a defective product and an occurrence of an underkill where a defective product is judged as a good product.

In contrast, for example, Patent Literature (PTL) 1 proposes an image classification method that automatically classifies images of detected faults in appearance inspections.

However, a seepage defect in a pixel region of an organic EL display panel is not taken into consideration as a type of fault in PTL 1. In other words, the image classification method according to PTL 1 can only classify foreign substances, defects, and bubbles as types of faults and is unable to classify seepage defects in the pixel region of an organic EL display panel.

The present disclosure has been made in consideration of the situation described above and an object thereof is to provide an inspection method and the like which enable a determination of a fault mode in a pixel region of a display panel to be automatically performed.

In order to achieve the object described above, an inspection method according to an aspect of the present disclosure is an inspection method to be performed by a computer for inspecting a display panel, the inspection method including: obtaining an anomalous portion image that is an image including an anomalous portion of a pixel region of the display panel, the anomalous portion being acquired by performing image processing using a background subtraction method on an inspection image of the pixel region; generating, using a trained generative model, a label image from the anomalous portion image by converting a region indicating the anomalous portion into a region of a color corresponding to a fault mode of the anomalous portion; and determining, based on the color of the region in the label image, whether the fault mode of the anomalous portion has a possibility of being a seepage defect in which light is not emitted due to deterioration of a functional layer in the pixel region, wherein the fault mode includes the seepage defect and a dark-dot defect in which light is not emitted due to an electrical short circuit or an electrical open circuit in the pixel region.

Accordingly, a determination of a fault mode in a pixel region of a display panel can be automatically performed.

In addition, the inspection method may further include, prior to the determining, obtaining a classification result from the anomalous portion image by using a trained convolutional neural network (CNN) model, the classification result indicating the fault mode of the anomalous portion, and in the determining, whether the fault mode of the anomalous portion has the possibility of being the seepage defect may be determined based on the classification result obtained in the obtaining of the classification result and the color of the region in the label image.

In addition, for example, in the determining, whether the fault mode of the anomalous portion has the possibility of being the seepage defect may be determined by the computer when the fault mode indicated by the classification result obtained in the obtaining of the classification result and the fault mode indicated by the color of the region in the label image are identical, and when the fault modes are not identical, a notification that the fault modes are not identical may be made to cause an operator to determine whether the fault mode of the anomalous portion has the possibility of being the seepage defect, the inspection method may further include: measuring a size of the region in the label image to determine whether the size measured is greater than or equal to a predetermined value when, in the determining, the fault mode of the anomalous portion is determined to have the possibility of being the seepage defect; and determining that the fault mode of the anomalous portion is the seepage defect when the size of the region is determined, in the measuring, to be greater than or equal to the predetermined value.

In addition, for example, the inspection method may include: measuring a size of the region in the label image to determine whether the size measured is greater than or equal to a predetermined value when, in the determining, the fault mode of the anomalous portion is determined to have the possibility of being the seepage defect; and determining that the fault mode of the anomalous portion is the seepage defect when the size of the region is determined, in the measuring, to be greater than or equal to the predetermined value.

In addition, for example, the trained generative model is trained using (i) an anomalous portion image for training that is obtained by performing image processing using the background subtraction method on an inspection image of the pixel region of the display panel and (ii) a label image for training that is obtained by converting a region indicating an anomalous portion shown in the anomalous portion image for training, into a region of a color corresponding to a fault mode of the anomalous portion, the anomalous portion image for training and the label image for training being prepared as teaching data, and the fault mode of the anomalous portion indicates the dark-dot defect, the seepage defect, or a normal state.

Here, for example, the trained generative model may be a generative adversarial networks (GAN)-based neural network model. In addition, for example, the trained generative model may be a Pix2Pix neural network model.

In addition, for example, the anomalous portion image for training may be subjected to histogram adjustment to make a background region uniformly white, the background region excluding the region indicating the anomalous portion.

Note that these general or specific aspects may be implemented as a device, a method, an integrated circuit, a computer program, a computer-readable recording medium such as a compact disc read-only memory (CD-ROM), or as any combination of systems, methods, integrated circuits, computer programs, and recording media.

The present disclosure can provide an inspection method and the like which enable a determination of a fault mode in a pixel region of a display panel to be automatically performed.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that each of the embodiments described below shows a specific example of the present disclosure. The numerical values, shapes, materials, standards, constituent elements, the arrangement and connection of the constituent elements, steps, the processing order of the steps, etc., indicated in the embodiments below are mere examples, and do not intend to limit the present disclosure. Also, among the constituent elements in the embodiments below, those not recited in any one of the independent claims of the present disclosure will be described as optional elements. Furthermore, each drawing is not necessarily a strict representation. In the drawings, the same reference signs are given to substantially the same elements, and duplicate description may be omitted or simplified.

Hereinafter, an inspection device and the like according to the present embodiment will be described.

Hereinafter, inspection deviceaccording to the present embodiment will be described with reference to the drawings.

is a diagram illustrating a schematic configuration of an inspection system including inspection deviceaccording to the present embodiment. In the present embodiment, a case where an inspection object of inspection deviceis organic EL display panelwill be described as an example. The inspection object of inspection devicemay be a display panel using a quantum dot light-emitting diode (QLED).

The inspection system illustrated inincludes inspection device, imaging device, stage, and stage driver.

Inspection deviceis a device for automatically performing a DS inspection which inspects whether or not a seepage defect is present in a pixel region of organic EL display panel. As described earlier, a seepage defect is a black stain-like display defect caused by faults in a moisture barrier layer. More specifically, the seepage defect according to the present embodiment is a display defect in which light is not emitted due to a degradation of functional layers including a light-emitting layer in the pixel region and is one of the fault modes. Typically, a degradation of functional layers including the light-emitting layer is caused by moisture. In addition, the seepage defect often appears as a display defect in which moisture has seeped to the light-emitting layer in the pixel region. In other words, the seepage defect appears as a defect in which a region (seepage region) where moisture has seeped into the light-emitting layer of organic EL display panelappears in an enlarged image of the pixel region and the size of the seepage region equals or exceeds a predetermined value. A mechanism of occurrence of seepage defects will be described later.

Imaging devicecaptures images of an inspection object region on organic EL display paneland is constituted of a CCD (Charge Coupled Device) or a CMOS (Complementary Metal-Oxide Semiconductor). More specifically, imaging deviceacquires an inspection image of organic EL display panelby capturing a pixel region that is an inspection object region on organic EL display panel. Note that imaging deviceis controlled by inspection device, and, alternatively, imaging devicemay be controlled by another computer.

Stageholds organic EL display panel.

Stage driveris constituted of a ball screw, a guide rail, and a motor and relatively moves stagewith respect to imaging device. Note that stage driveris controlled by inspection device, and, alternatively, stage drivermay be controlled by another computer.

are examples of enlarged images of inspection images used in a DS inspection according to the present embodiment.illustrates an example of a case where a seepage region that constitutes a seepage defect appears in enlarged imageof a pixel region of organic EL display panel. In addition,illustrates an example of a case where dark dots (dark-dot region) that constitutes a dark-dot defect appears in enlarged imageof a pixel region of organic EL display panel. Note that dark dots are light-emitting pixels that do not emit light (is not lighted) due to an electrical short circuit or an electrical open circuit of the pixel region, and dark dots may include light-emitting pixels with low emission luminance.

Note that when the operator performs the DS inspection himself/herself, the operator is to identify whether or not a seepage region or dark dots appear in the enlarged image of the pixel region by a contour shape. Since the seepage region is a region where moisture seeps to a light-emitting layer of the pixel region and where a region where the moisture seeps grows and becomes larger over time or the like, the seepage region has a smooth contour and can be distinguished from a dark-dot region with a contour that is not smooth. However, it is difficult to distinguish contours from each other and, depending on the operator, a seepage region may be erroneously determined to be a dark-dot region.

is a schematic diagram for describing a mechanism of occurrence of a seepage defect.schematically illustrates an example of a sectional view of the pixel region of organic EL display panel. For example, as illustrated in, organic EL display panelincludes glass substrate, thin-film transistor layerformed on glass substrate, light-emitting layerformed on thin-film transistor layer, and protective filmformed on light-emitting layer. Protective filmfunctions as a moisture barrier layer for blocking moisture. In addition, in organic EL display panel, an upper substrate is formed on protective filmvia fillersuch as an adhesive. In the example illustrated in, the upper substrate is formed of color filter layerand glass substrate. Furthermore, color filter layerincludes a black matrix (BM) that partitions a pixel region and the pixel region. Note that the upper substrate may be a substrate constituted of a flexible polarizing plate or the like.

As illustrated in, it is assumed that, when forming protective filmof organic EL display panel, foreign substanceis included in protective filmand a gap is created in protective film. In other words, it is assumed that a fault of the moisture barrier layer has occurred in organic EL display panel. Then, moisture that is indicated as HO infalls from color filter layeror the like to protective film. Note that moisture may include moisture contained in fillerin addition to moisture included in color filter layer. Next, the moisture having fallen on protective filmpenetrates into the gap in protective filmand adsorbs on light-emitting layer. In this manner, the moisture having fallen on protective filmpenetrates into protective filmthrough penetration pathand adsorbs on light-emitting layer. Furthermore, for example, a moisture adsorption area progresses in a direction of arrowor, in other words, along light-emitting layer. In this manner, a region where moisture seeps spreads to the light-emitting layer of the pixel region. Note that since heat is a dominant factor promoting progression, the region of seepage expands with temperature and time. Therefore, the size of the seepage region that becomes defective at the time of DS inspection is determined based on the size of the seepage region that can be treated as a good product at an end of a product lifetime of the organic EL display panel. In this case, the size of the seepage region that becomes defective at the time of DS inspection is, for example, in the order of several ten microns.

illustrate examples of the sizes of seepage regions that appear in enlarged images of inspection images used in the DS inspection according to the present embodiment.illustrate the sizes of seepage regions that appear in enlarged images of a pixel region of organic EL display panel.

Note that when the operator performs the DS inspection himself/herself, the operator is to measure the size of the seepage region that appears in an enlarged image of the pixel region. However, as illustrated in, since the seepage region is partially blocked by the partition between pixels or, in other words, the BM, it is difficult for the operator to recognize an end of the seepage region. As a result, depending on the operator, a variation is created in the measurement of the size of the seepage region.

Before describing a functional configuration of inspection deviceaccording to the present embodiment, an example of a hardware configuration of inspection deviceaccording to the present embodiment will be described using.

is a diagram illustrating an example of a hardware configuration of computerthat realizes functions of inspection deviceaccording to the present embodiment by software.

As illustrated in, computeris a computer including input device, output device, CPU, internal storage, RAM, GPU, reading device, transmission and reception device, and bus. Input device, output device, CPU, internal storage, RAM, GPU, reading device, and transmission and reception deviceare connected by bus.

Input deviceis a device to be a user interface such as an input button, a touch pad, or a touch panel display and accepts operations by a user. Note that in addition to accepting contact operations of the user, input devicemay be configured to accept operations by voice, remote operations using a remote controller, and the like.

Output deviceis used in conjunction with input deviceand is constituted of a touch pad or a touch panel display, and the like, and notifies the user of information that the user should be aware of.

Internal storageis a flash memory or the like. In addition, internal storagemay store, in advance, at least one of a program for realizing the functions of inspection deviceand an application using the functional configuration of inspection device. Furthermore, internal storagemay store a neural network model (such as a generative model), acquired training data, parameters such as intermediate layers of the model, procedures for performing image processing such as a background subtraction method, procedures for performing determinations such as a non-dark-dot defect determination and a DS determination to be described later, and the like.

RAMis a random access memory and is used to store data and the like when executing the program or the application.

GPUis a graphics processing unit that copies a program, an application, and data stored in internal storageto a dedicated RAM built into the GPU and executes graphics processing according to instructions contained in the program or application.

Reading devicereads information from a recording medium such as a USB (Universal Serial Bus) memory. Reading devicereads the program or the application described above from a recording medium in which the program or the application is recorded and causes the program or the application to be stored in internal storage.

Transmission and reception deviceis a communication circuit for performing wireless or wired communication. Transmission and reception devicemay communicate with, for example, a server device connected to a network to download the program or the application described above from the server device and store the program or the application in internal storage.

CPUis a central processing unit that copies a program or an application stored in internal storageto RAM, sequentially reads instructions contained in the program or the application from RAM, and executes the instructions.

Next, each functional element of inspection deviceaccording to the present embodiment will be described using.

is a block diagram illustrating an example of a functional configuration of inspection deviceaccording to the present embodiment.

As illustrated in, inspection deviceincludes image obtainer, label image generator, non-dark-dot defect determiner, size measurer, and DS determiner. Note that size measurerand DS determinerare not essential in inspection deviceand may be provided outside of inspection device.

Image obtainerobtains an anomalous portion image that is an image including an anomalous portion of a pixel region of organic EL display panel. Here, the anomalous portion is acquired by performing image processing using a background subtraction method on an inspection image of the pixel region.

In the present embodiment, image obtainerobtains, from imaging device, an inspection image of a pixel region of organic EL display panelto be used in a DS inspection. In addition, image obtainerperforms image processing using a background subtraction method on the obtained inspection image and generates an anomalous portion image that is a background subtraction image including an anomalous portion of a pixel region of organic EL display panel. Note that image obtainercan realize various functions such as an inspection image obtaining function, an image processing function, and an anomalous portion image generation function by having a processor execute a control program stored in a memory in a computer that realizes the functions of inspection device.